互感预测编码,主动推断和催眠暗示响应的生成
1School of Psychology, Faculty of Medicine and Health, University of New England, Armidale, NSW, Australia.
International review of neurobiology
|November 16, 2025
概括
贝叶斯预测编码模型为理解催眠机制提供了一个统一的框架. 这种方法在催眠研究中产生可测试的心理,生理和临床结果的预测.
科学领域:
- 神经科学是一个神经科学.
- 认知心理学 认知心理学
- 计算精神病学是一种计算精神病学.
背景情况:
- 催眠研究从具有可测试预测的竞争理论模型中受益.
- 神经计算理论正在统一各种研究领域,并进入催眠领域.
研究的目的:
- 探索贝叶斯预测编码模型,以了解催眠暗示机制.
- 展示预测编码作为催眠理论的统一框架.
- 从这些模型中得出可测试的神经生理学预测.
主要方法:
- 使用贝叶斯预测编码模型.
- 应用主动推理机制.
- 在预测编码框架内比较当前的催眠理论 (分离控制,吸收,响应期望).
主要成果:
- 预测编码为催眠反应的多种可测试解释提供了一个框架.
- 当前的催眠理论可以在这个统一的框架内建模.
- 主动推理在产生独特的神经生理学预测方面发挥着核心作用.
结论:
- 贝叶斯预测编码为推进催眠研究提供了一个强大的框架.
- 这种方法促进了对心理和临床结果的可测试假设的开发.
- 它为未来的催眠和相关现象的研究和赠款资助奠定了基础.
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